Evaluate AI-assisted ad creation

Q: Evaluate AI-assisted ad creation

This question evaluates competency in product analytics, experimentation design, causal inference, metric definition, and measurement of downstream business and user-quality impacts for an AI-assisted advertising feature.

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Question

Meta is considering launching an AI-assisted ad creation feature for advertisers. The feature helps advertisers generate ad copy and/or creatives inside the ad creation flow. The product team wants to know whether the feature creates real value, not just whether people click on it.

How would you evaluate whether this feature should launch?

Please address:

The product objective and the primary success metric(s)
A full metric set across advertiser adoption, campaign creation, downstream ad performance, platform revenue, and user-quality guardrails
An experiment design, including the unit of randomization, test duration, and how you would handle the fact that usage of the feature may be optional
How you would distinguish incremental impact from simple cannibalization of existing ad creation tools or sources
Key risks such as selection bias, interference through the ad auction, novelty effects, and heterogeneous treatment effects across advertiser segments

Evaluate AI-assisted ad creation

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